Science bridges political barriers.

Aya Awad is a graduate of the Science Training Encouraging Peace (STEP) program. The STEP program funds pairs of Israeli and Palestinian students to study together for the length of their graduate degrees. She writes about the friendship she developed with her STEP partner and how science bridged political barriers.

Salmonella manipulates the host to drive pathogenicity via induction of interleukin 1ß.

Acute gastrointestinal infection with intracellular pathogens like Salmonella Typhimurium triggers the release of the proinflammatory cytokine interleukin 1ß (IL-1ß). However, the role of IL-1ß in intestinal defense against Salmonella remains unclear. Here, we show that IL-1ß production is detrimental during Salmonella infection. Mice lacking IL-1ß (IL-1ß -/-) failed to recruit neutrophils to the gut during infection, which reduced tissue damage and prevented depletion of short-chain fatty acid (SCFA)-producing commensals. Changes in epithelial cell metabolism that typically support pathogen expansion, such as switching energy production from fatty acid oxidation to fermentation, were absent in infected IL-1ß -/- mice which inhibited Salmonella expansion. Additionally, we found that IL-1ß induces expression of complement anaphylatoxins and suppresses the complement-inactivator carboxypeptidase N (CPN1). Disrupting this process via IL-1ß loss prevented mortality in Salmonella-infected IL-1ß -/- mice. Finally, we found that IL-1ß expression correlates with expression of the complement receptor in patients suffering from sepsis, but not uninfected patients and healthy individuals. Thus, Salmonella exploits IL-1ß signaling to outcompete commensal microbes and establish gut colonization. Moreover, our findings identify the intersection of IL-1ß signaling and the complement system as key host factors involved in controlling mortality during invasive Salmonellosis.

Inherited human Apollo deficiency causes severe bone marrow failure and developmental defects.

Inherited bone marrow failure syndromes (IBMFSs) are a group of disorders typified by impaired production of 1 or several blood cell types. The telomere biology disorders dyskeratosis congenita (DC) and its severe variant, Høyeraal-Hreidarsson (HH) syndrome, are rare IBMFSs characterized by bone marrow failure, developmental defects, and various premature aging complications associated with critically short telomeres. We identified biallelic variants in the gene encoding the 5'-to-3' DNA exonuclease Apollo/SNM1B in 3 unrelated patients presenting with a DC/HH phenotype consisting of early-onset hypocellular bone marrow failure, B and NK lymphopenia, developmental anomalies, microcephaly, and/or intrauterine growth retardation. All 3 patients carry a homozygous or compound heterozygous (in combination with a null allele) missense variant affecting the same residue L142 (L142F or L142S) located in the catalytic domain of Apollo. Apollo-deficient cells from patients exhibited spontaneous chromosome instability and impaired DNA repair that was complemented by CRISPR/Cas9-mediated gene correction. Furthermore, patients' cells showed signs of telomere fragility that were not associated with global reduction of telomere length. Unlike patients' cells, human Apollo KO HT1080 cell lines showed strong telomere dysfunction accompanied by excessive telomere shortening, suggesting that the L142S and L142F Apollo variants are hypomorphic. Collectively, these findings define human Apollo as a genome caretaker and identify biallelic Apollo variants as a genetic cause of a hitherto unrecognized severe IBMFS that combines clinical hallmarks of DC/HH with normal telomere length.

Clinical and genetic factors associated with self-reported cognitive deficits in women with breast cancer: the "CAGE-Cog" study.

BACKGROUND: Breast cancer patients undergoing chemotherapy treatment are at particular risk of experiencing acute cognitive impairment leading to daily challenges in decision-making and reduced quality of life and functional autonomy. The aim was to assess the relationship between clinical and genetic factors and cognitive function in a sample of patients with breast cancer undergoing chemotherapy. METHODS: A cross-sectional study was carried out between November 2017 and June 2019 on women (N = 112) treated for breast cancer by intravenous chemotherapy at the oncology outpatient unit of Hôtel-Dieu de France Hospital, Beirut. Patients were evaluated with the 37-item Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog). Other validated scales were also used to assess depression, anxiety, sleep disorders, pain, and fatigue. DNA was obtained by a buccal swab (FTA®technology) for genotyping of different genes (ABCB1, COMT, DRD2, OPRM1, CLOCK, CRY2, and PER2) using the Lightcycler®(Roche). RESULTS: The mean age of participants was 56.04 years. Multivariable analysis, taking the four FACT-Cog subscores as the dependent variables, showed that the mean cognitive score decreased with higher depression, anxiety, and insomnia scores. Patients with university education levels had better perceived cognitive abilities than those with primary education. Moreover, carrying the G allele for the OPRM1 polymorphism (c.118A > G;rs197791) was significantly associated with a better cognitive function compared to AA patients (B = 2.05; p = 0.038). CONCLUSIONS: A comprehensive oncological care plan should include a personalized assessment of all factors related to cognitive functioning in cancer patients, particularly anxiety and depression, to achieve an optimal patient outcome.

Full length RTEL1 is required for the elongation of the single-stranded telomeric overhang by telomerase.

Telomeres cap the ends of eukaryotic chromosomes and distinguish them from broken DNA ends to suppress DNA damage response, cell cycle arrest and genomic instability. Telomeres are elongated by telomerase to compensate for incomplete replication and nuclease degradation and to extend the proliferation potential of germ and stem cells and most cancers. However, telomeres in somatic cells gradually shorten with age, ultimately leading to cellular senescence. Hoyeraal-Hreidarsson syndrome (HHS) is characterized by accelerated telomere shortening and diverse symptoms including bone marrow failure, immunodeficiency, and neurodevelopmental defects. HHS is caused by germline mutations in telomerase subunits, factors essential for its biogenesis and recruitment to telomeres, and in the helicase RTEL1. While diverse phenotypes were associated with RTEL1 deficiency, the telomeric role of RTEL1 affected in HHS is yet unknown. Inducible ectopic expression of wild-type RTEL1 in patient fibroblasts rescued the cells, enabled telomerase-dependent telomere elongation and suppressed the abnormal cellular phenotypes, while silencing its expression resulted in gradual telomere shortening. Our observations reveal an essential role of the RTEL1 C-terminus in facilitating telomerase action at the telomeric 3' overhang. Thus, the common etiology for HHS is the compromised telomerase action, resulting in telomere shortening and reduced lifespan of telomerase positive cells.

An RTEL1 Mutation Links to Infantile-Onset Ulcerative Colitis and Severe Immunodeficiency.

PURPOSE: More than 50 different monogenic disorders causing inflammatory bowel disease (IBD) have been identified. Our goal was to characterize the clinical phenotype, genetic workup, and immunologic alterations in an Ashkenazi Jewish patient that presented during infancy with ulcerative colitis and unique clinical manifestations. METHODS: Immune workup and whole-exome sequencing were performed, along with Sanger sequencing for confirmation. Next-generation sequencing of the TCRB and IgH was conducted for immune repertoire analysis. Telomere length was evaluated by in-gel hybridization assay. Mass cytometry was performed on patient's peripheral blood mononuclear cells, and compared with control subjects and patients with UC. RESULTS: The patient presented in infancy with failure to thrive and dysmorphic features, consistent with a diagnosis of dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. Severe ulcerative colitis manifested in the first year of life and proceeded to the development of a primary immunodeficiency, presenting as Pneumocystis jiroveci pneumonia and hypogammaglobulinemia. Genetic studies identified a deleterious homozygous C.3791G>A missense mutation in the helicase regulator of telomere elongation 1 (RTEL1), leading to short telomeres in the index patient. Immune repertoire studies showed polyclonal T and B cell receptor distribution, while mass cytometry analysis demonstrated marked immunological alterations, including a predominance of naïve T cells, paucity of B cells, and a decrease in various innate immune subsets. CONCLUSIONS: RTEL1 mutations are associated with significant alterations in immune landscape and can manifest with infantile-onset IBD. A high index of suspicion is required in Ashkenazi Jewish families where the carriage rate of the C.3791G>A variant is high.

Human RTEL1 stabilizes long G-overhangs allowing telomerase-dependent over-extension.

Telomere maintenance protects the cell against genome instability and senescence. Accelerated telomere attrition is a characteristic of premature aging syndromes including Dyskeratosis congenita (DC). Mutations in hRTEL1 are associated with a severe form of DC called Hoyeraal-Hreidarsson syndrome (HHS). HHS patients carry short telomeres and HHS cells display telomere damage. Here we investigated how hRTEL1 contributes to telomere maintenance in human primary as well as tumor cells. Transient depletion of hRTEL1 resulted in rapid telomere shortening only in the context of telomerase-positive cells with very long telomeres and high levels of telomerase. The effect of hRTEL1 on telomere length is telomerase dependent without impacting telomerase biogenesis or targeting of the enzyme to telomeres. Instead, RTEL1 depletion led to a decrease in both G-overhang content and POT1 association with telomeres with limited telomere uncapping. Strikingly, overexpression of POT1 restored telomere length but not the overhang, demonstrating that G-overhang loss is the primary defect caused by RTEL1 depletion. We propose that hRTEL1 contributes to the maintenance of long telomeres by preserving long G-overhangs, thereby facilitating POT1 binding and elongation by telomerase.

The many faces of the helicase RTEL1 at telomeres and beyond.

Regulator of telomere elongation 1 (RTEL1) is known as a DNA helicase that is important for telomeres and genome integrity. However, the diverse phenotypes of RTEL1 dysfunction, the wide spectrum of symptoms caused by germline RTEL1 mutations, and the association of RTEL1 mutations with cancers suggest that RTEL1 is a complex machine that interacts with DNA, RNA, and proteins, and functions in diverse cellular pathways. We summarize the proposed functions of RTEL1 and discuss their implications for telomere maintenance. Studying RTEL1 is crucial for understanding the complex interplay between telomere maintenance and other nuclear pathways, and how compromising these pathways causes telomere biology diseases, various aging-associated pathologies, and cancer.

The analgesic effect of transmuscular quadratus lumborum block versus erector spinae plane block for women undergoing elective Caesarean section: A randomized controlled trial.

Background: We aimed to compare the analgesic effect and quality of recovery of transmuscular quadratus lumborum block (QLB) and erector spinae plane block (ESPB) in the presence of multimodal analgesia following Caesarean section. Methods: This randomised controlled trial included full-term pregnant women who underwent elective Caesarean section under spinal anaesthesia without intrathecal morphine. The included women were randomised to receive either bilateral QLB (n = 51) or bilateral thoracic ESPB (n = 51), in addition to the control group (n = 51) who did not receive any block. All participants received regular paracetamol (1 g/6h) and diclofenac (50 mg/8 h). Intravenous morphine was used as a rescue analgesic. The primary outcome was time to first morphine requirement. Secondary outcomes included total postoperative morphine consumption and total Obstetric Quality of Recovery-11 (ObsQoR-11) score. Results: We analysed 51, 50 and 48 patients in the QLB, ESPB and control groups, respectively. The time to first morphine requirement in both QLB and ESPB groups was longer than that in the control group (median [quartiles] time: 6 [6,12] h, 6 [6,6] h and 4 [3,4] h, respectively; p-value <0.001), without significant differences between the two former groups. The total morphine consumption in both QLB and ESPB groups was lower than that in the control group (median [quartiles]:0 [0,5] mg, 0 [0,5] mg and 25 [25,30] mg, respectively; p-value <0.001), without significant differences between the two former groups. The QLB and ESPB groups had comparable ObsQoR-11 score, and both groups' scores were higher than the control group. Conclusion: In patients undergoing elective Caesarean section under spinal anaesthesia without intrathecal morphine, both QLB and ESPB provided superior analgesia and quality of recovery compared to the standard care, without significant difference between the two blocks.

Bioactive compounds, pharmacological actions and pharmacokinetics of Cupressus sempervirens.

The roles of plants and its products in all forms of life cannot be overemphasized. The medicinal products from plant are phytochemicals, drugs, food supplements, beauty products, etc. In ethnomedicine, leaves, fruits, stem, bark, root and fluids from plants are used in the cure, management and prevention of several diseases. Cupressus sempervirens, sometimes called Italian or Mediterranean cypress, is found in subtropical Asia, North America and eastern Mediterranean region. Pharmacological investigations of Cupressus sempervirens showed biological properties such as aromatherapeutic, antiseptic, astringent, balsamic or anti-inflammatory, astringent, antiperspirant, diuretic and antispasmodic. Chemical analysis of Cupressus sempervirens gives phytochemicals like monoterpenes, diterpenes, flavonoid glycosides and bioflavonoids. The current review highlights interactions, conventional uses and biological actions of Cupressus sempervirens plant and plant products.

Autophagy controls mucus secretion from intestinal goblet cells by alleviating ER stress.

Colonic goblet cells are specialized epithelial cells that secrete mucus to physically separate the host and its microbiota, thus preventing bacterial invasion and inflammation. How goblet cells control the amount of mucus they secrete is unclear. We found that constitutive activation of autophagy in mice via Beclin 1 enables the production of a thicker and less penetrable mucus layer by reducing endoplasmic reticulum (ER) stress. Accordingly, genetically inhibiting Beclin 1-induced autophagy impairs mucus secretion, while pharmacologically alleviating ER stress results in excessive mucus production. This ER-stress-mediated regulation of mucus secretion is microbiota dependent and requires the Crohn's-disease-risk gene Nod2. Overproduction of mucus alters the gut microbiome, specifically expanding mucus-utilizing bacteria, such as Akkermansia muciniphila, and protects against chemical and microbial-driven intestinal inflammation. Thus, ER stress is a cell-intrinsic switch that limits mucus secretion, whereas autophagy maintains intestinal homeostasis by relieving ER stress.

Air-assisted cloud point extraction coupled with inductively coupled plasma optical emission spectroscopy for determination of samarium in environmental samples.

For the first time, air-assisted cloud point extraction (AACPE) was presented to preconcentrate metal ions. The procedure was conjugated with inductively coupled plasma-optical emission spectroscopy for determination of samarium. In this procedure, samarium ions were complexed with aluminon and extracted into Triton X-114 in the presence of potassium iodide. The mixture was repeatedly sucked and dispersed with a syringe (three times) to create cloud solution. Experimental factors that affect the extraction competence of the AACPE procedure, such as pH, amount of aluminon and Triton X-114, salt addition, number of suction/injection cycles, and centrifugation rate and time, have been investigated and optimized. A linear calibration curve from 0.2 to 200.0 µg L-1 with enrichment factor and detection limit of 102 and 0.06 µg L-1, respectively, was established under the optimum experimental conditions. The approach was used to determine samarium in wastewater and rock samples, with recoveries ranging from 98% to 99%.

An acetylated derivative of vitexin halts MDA-MB-231 cellular progression and improves its immunogenic profile through tuning miR- 20a-MICA/B axis.

The activating immune ligands, MICA/B, act as a "kill me" signal through the NKG2D receptor expressed on natural killer (NK) cells. Recently, the oncogenic miR-20a was found to mediate immune escape through repressing MICA/B levels in breast cancer (BC) cells. However, targeting miR-20a-MICA/B using natural compounds has rarely been investigated. Our group has successfully isolated 3'-O-acetylvitexin that showed cytotoxic effects against colon cancer cells but has never been evaluated in BC. Our aim is to investigate the effects of 3'-O-acetylvitexin on BC cell lines and to further elucidate its molecular mechanism of action.The results showed that 3'-O-acetylvitex depicted a more pronounced dose-dependent repression of TNBC cellular viability, colonogenicity and migration capacity than Vitexin. 3'-O-acetylvitexin treatment resulted in a marked dose-dependent repression of miR-20a with a concomitant dose-dependent increase in MICA/B expression. In conclusion, 3'-O-acetylvitexin might act as a promising therapeutic agent for TNBC patients.

Management of SARS-CoV-2 Infection: Key Focus in Macrolides Efficacy for COVID-19.

Macrolides (e.g., erythromycin, fidaxomicin, clarithromycin, and azithromycin) are a class of bacteriostatic antibiotics commonly employed in medicine against various gram-positive and atypical bacterial species mostly related to respiratory tract infections, besides they possess anti-inflammatory and immunomodulatory effects. Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2). It was first detected in Wuhan, Hubei, China, in December 2019 and resulted in a continuing pandemic. Macrolides have been extensively researched as broad adjunctive therapy for COVID-19 due to its immunostimulant abilities. Among such class of drugs, azithromycin is described as azalide and is well-known for its ability to decrease the production of pro-inflammatory cytokines, including matrix metalloproteinases, tumor necrosis factor-alpha, interleukin (IL)-6, and IL-8. In fact, a report recently published highlighted the effectiveness of combining azithromycin and hydroxychloroquine for COVID-19 treatment. Indeed, it has been underlined that azithromycin quickly prevents SARS-CoV-2 infection by raising the levels of both interferons and interferon-stimulated proteins at the same time which reduces the virus replication and release. In this sense, the current review aims to evaluate the applications of macrolides for the treatment of COVID-19.

Predicting hospital mortality for intensive care unit patients: Time-series analysis.

Current mortality prediction models and scoring systems for intensive care unit patients are generally usable only after at least 24 or 48 h of admission, as some parameters are unclear at admission. However, some of the most relevant measurements are available shortly following admission. It is hypothesized that outcome prediction may be made using information available in the earliest phase of intensive care unit admission. This study aims to investigate how early hospital mortality can be predicted for intensive care unit patients. We conducted a thorough time-series analysis on the performance of different data mining methods during the first 48 h of intensive care unit admission. The results showed that the discrimination power of the machine-learning classification methods after 6 h of admission outperformed the main scoring systems used in intensive care medicine (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score and Sequential Organ Failure Assessment) after 48 h of admission.

Patient length of stay and mortality prediction: A survey.

Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance, in particular hospitals want to improve their intensive care unit statistics by reducing the number of patients dying inside the intensive care unit. Research has focused on prediction of measurable outcomes, including risk of complications, mortality and length of hospital stay. The length of stay is an important metric both for healthcare providers and patients, influenced by numerous factors. In particular, the length of stay in critical care is of great significance, both to patient experience and the cost of care, and is influenced by factors specific to the highly complex environment of the intensive care unit. The length of stay is often used as a surrogate for other outcomes, where those outcomes cannot be measured; for example as a surrogate for hospital or intensive care unit mortality. The length of stay is also a parameter, which has been used to identify the severity of illnesses and healthcare resource utilisation. This paper examines a range of length of stay and mortality prediction applications in acute medicine and the critical care unit. It also focuses on the methods of analysing length of stay and mortality prediction. Moreover, the paper provides a classification and evaluation for the analytical methods of the length of stay and mortality prediction associated with a grouping of relevant research papers published in the years 1984 to 2016 related to the domain of survival analysis. In addition, the paper highlights some of the gaps and challenges of the domain.

Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

BACKGROUND: Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission. OBJECTIVES: This study highlights the main data challenges in early mortality prediction in ICU patients and introduces a new machine learning based framework for Early Mortality Prediction for Intensive Care Unit patients (EMPICU). MATERIALS AND METHODS: The proposed method is evaluated on the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Mortality prediction models are developed for patients at the age of 16 or above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU). We employ the ensemble learning Random Forest (RF), the predictive Decision Trees (DT), the probabilistic Naive Bayes (NB) and the rule-based Projective Adaptive Resonance Theory (PART) models. The primary outcome was hospital mortality. The explanatory variables included demographic, physiological, vital signs and laboratory test variables. Performance measures were calculated using cross-validated area under the receiver operating characteristic curve (AUROC) to minimize bias. 11,722 patients with single ICU stays are considered. Only patients at the age of 16 years old and above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU) are considered in this study. RESULTS: The proposed EMPICU framework outperformed standard scoring systems (SOFA, SAPS-I, APACHE-II, NEWS and qSOFA) in terms of AUROC and time (i.e. at 6h compared to 48h or more after admission). DISCUSSION AND CONCLUSION: The results show that although there are many values missing in the first few hour of ICU admission, there is enough signal to effectively predict mortality during the first 6h of admission. The proposed framework, in particular the one that uses the ensemble learning approach - EMPICU Random Forest (EMPICU-RF) offers a base to construct an effective and novel mortality prediction model in the early hours of an ICU patient admission, with an improved performance profile.